Face Generation

In this project, you'll use generative adversarial networks to generate new images of faces.

Get the Data

You'll be using two datasets in this project:

  • MNIST
  • CelebA

Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.

If you're using FloydHub, set data_dir to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".

In [2]:
data_dir = './data'

# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'


"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper

helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
Found mnist Data
Found celeba Data

Explore the Data

MNIST

As you're aware, the MNIST dataset contains images of handwritten digits. You can view the first number of examples by changing show_n_images.

In [3]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot

mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
Out[3]:
<matplotlib.image.AxesImage at 0x6cd263eeb8>

CelebA

The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images.

In [4]:
show_n_images = 25

"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Out[4]:
<matplotlib.image.AxesImage at 0x6cd36c1e10>

Preprocess the Data

Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

The MNIST images are black and white images with a single color channel while the CelebA images have 3 color channels (RGB color channel).

Build the Neural Network

You'll build the components necessary to build a GANs by implementing the following functions below:

  • model_inputs
  • discriminator
  • generator
  • model_loss
  • model_opt
  • train

Check the Version of TensorFlow and Access to GPU

This will check to make sure you have the correct version of TensorFlow and access to a GPU

In [5]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf

# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer.  You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))

# Check for a GPU
if not tf.test.gpu_device_name():
    warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
    print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
TensorFlow Version: 1.0.0
C:\Anaconda3\envs\ai\lib\site-packages\ipykernel_launcher.py:14: UserWarning: No GPU found. Please use a GPU to train your neural network.
  

Input

Implement the model_inputs function to create TF Placeholders for the Neural Network. It should create the following placeholders:

  • Real input images placeholder with rank 4 using image_width, image_height, and image_channels.
  • Z input placeholder with rank 2 using z_dim.
  • Learning rate placeholder with rank 0.

Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)

In [6]:
import problem_unittests as tests

def model_inputs(image_width, image_height, image_channels, z_dim):
    """
    Create the model inputs
    :param image_width: The input image width
    :param image_height: The input image height
    :param image_channels: The number of image channels
    :param z_dim: The dimension of Z
    :return: Tuple of (tensor of real input images, tensor of z data, learning rate)
    """
    # TODO: Implement Function
    input_real = tf.placeholder(tf.float32, shape=[None, image_width, image_height, image_channels], name='input_real')
    input_z = tf.placeholder(tf.float32, shape=[None, z_dim], name='input_z')
    lr = tf.placeholder(tf.float32, name='learning_rate')
    return input_real, input_z, lr


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Tests Passed

Discriminator

Implement discriminator to create a discriminator neural network that discriminates on images. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the discriminator, tensor logits of the discriminator).

In [7]:
def leaky_relu(input):
    return tf.maximum(0.1 * input, input)

def discriminator(images, reuse=False):
    """
    Create the discriminator network
    :param images: Tensor of input image(s)
    :param reuse: Boolean if the weights should be reused
    :return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
    """
    # TODO: Implement Function
    with tf.variable_scope('discriminator', reuse=reuse):        
        conv1 = tf.layers.conv2d(images, 56, 5, 2, 'same')
        conv1 = leaky_relu(conv1)
        
        conv2 = tf.layers.conv2d(conv1, 112, 5, 2, 'same')
        conv2 = tf.layers.batch_normalization(conv2, training=True)
        conv2 = leaky_relu(conv2)
        
        conv3 = tf.layers.conv2d(conv2, 224, 5, 2, 'same')
        conv3 = tf.layers.batch_normalization(conv3, training=True)
        conv3 = leaky_relu(conv3)
        
        flat = tf.reshape(conv3, (-1, 4*4*224))
        logits = tf.layers.dense(flat, 1)

        return tf.sigmoid(logits), logits


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Tests Passed

Generator

Implement generator to generate an image using z. This function should be able to reuse the variables in the neural network. Use tf.variable_scope with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim images.

In [8]:
def generator(z, out_channel_dim, is_train=True):
    """
    Create the generator network
    :param z: Input z
    :param out_channel_dim: The number of channels in the output image
    :param is_train: Boolean if generator is being used for training
    :return: The tensor output of the generator
    """
    # TODO: Implement Function
    with tf.variable_scope('generator', reuse=(not is_train)):        
        fc = tf.layers.dense(z, 7*7*112)
        fc = tf.reshape(fc, (-1, 7, 7, 112))
        fc = tf.layers.batch_normalization(fc, training=is_train)
        fc = leaky_relu(fc)
        
        conv1 = tf.layers.conv2d_transpose(fc, 56, 5, 2, 'same')
        conv1 = tf.layers.batch_normalization(conv1, training=is_train)
        conv1 = leaky_relu(conv1)
        
        conv2 = tf.layers.conv2d_transpose(conv1, out_channel_dim, 5, 2, 'same')
        
        return tf.tanh(conv2)

"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Tests Passed

Loss

Implement model_loss to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:

  • discriminator(images, reuse=False)
  • generator(z, out_channel_dim, is_train=True)
In [9]:
def model_loss(input_real, input_z, out_channel_dim):
    """
    Get the loss for the discriminator and generator
    :param input_real: Images from the real dataset
    :param input_z: Z input
    :param out_channel_dim: The number of channels in the output image
    :return: A tuple of (discriminator loss, generator loss)
    """
    # TODO: Implement Function
    
    g_model = generator(input_z, out_channel_dim)
    d_model_real, d_logits_real = discriminator(input_real)
    d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)

    d_loss_real = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, labels=tf.ones_like(d_model_real)))
    d_loss_fake = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
    g_loss = tf.reduce_mean(
        tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake, labels=tf.ones_like(d_model_fake)))

    d_loss = d_loss_real + d_loss_fake

    return d_loss, g_loss


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Tests Passed

Optimization

Implement model_opt to create the optimization operations for the GANs. Use tf.trainable_variables to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).

In [10]:
def model_opt(d_loss, g_loss, learning_rate, beta1):
    """
    Get optimization operations
    :param d_loss: Discriminator loss Tensor
    :param g_loss: Generator loss Tensor
    :param learning_rate: Learning Rate Placeholder
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :return: A tuple of (discriminator training operation, generator training operation)
    """
    # TODO: Implement Function
    t_vars = tf.trainable_variables()
    d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
    g_vars = [var for var in t_vars if var.name.startswith('generator')]

    # Optimize
    with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
        d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
        g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(g_loss, var_list=g_vars)

    return d_train_opt, g_train_opt


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
Tests Passed

Neural Network Training

Show Output

Use this function to show the current output of the generator during training. It will help you determine how well the GANs is training.

In [11]:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np

def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
    """
    Show example output for the generator
    :param sess: TensorFlow session
    :param n_images: Number of Images to display
    :param input_z: Input Z Tensor
    :param out_channel_dim: The number of channels in the output image
    :param image_mode: The mode to use for images ("RGB" or "L")
    """
    cmap = None if image_mode == 'RGB' else 'gray'
    z_dim = input_z.get_shape().as_list()[-1]
    example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])

    samples = sess.run(
        generator(input_z, out_channel_dim, False),
        feed_dict={input_z: example_z})

    images_grid = helper.images_square_grid(samples, image_mode)
    pyplot.imshow(images_grid, cmap=cmap)
    pyplot.show()

Train

Implement train to build and train the GANs. Use the following functions you implemented:

  • model_inputs(image_width, image_height, image_channels, z_dim)
  • model_loss(input_real, input_z, out_channel_dim)
  • model_opt(d_loss, g_loss, learning_rate, beta1)

Use the show_generator_output to show generator output while you train. Running show_generator_output for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator output every 100 batches.

In [12]:
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
    """
    Train the GAN
    :param epoch_count: Number of epochs
    :param batch_size: Batch Size
    :param z_dim: Z dimension
    :param learning_rate: Learning Rate
    :param beta1: The exponential decay rate for the 1st moment in the optimizer
    :param get_batches: Function to get batches
    :param data_shape: Shape of the data
    :param data_image_mode: The image mode to use for images ("RGB" or "L")
    """
    # TODO: Build Model
    steps = 0
    print_every = 10
    show_every = 10
    
    input_real, input_z, lr = model_inputs(data_shape[1], data_shape[2], data_shape[3], z_dim)
    d_loss, g_loss = model_loss(input_real, input_z, data_shape[3])
    d_opt, g_opt = model_opt(d_loss, g_loss, lr, beta1)
    
    with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())
        for epoch_i in range(epoch_count):
            for batch_images in get_batches(batch_size):
                # TODO: Train Model
                steps += 1
                batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
                _ = sess.run(d_opt, feed_dict={input_real: batch_images, input_z: batch_z, lr: learning_rate})
                _ = sess.run(g_opt, feed_dict={input_real: batch_images, input_z: batch_z, lr: learning_rate})
                
                if steps % print_every == 0:
                    train_loss_d = d_loss.eval(feed_dict={input_z: batch_z, input_real: batch_images})
                    train_loss_g = g_loss.eval(feed_dict={input_z: batch_z})
                    print("Epoch {}/{}...".format(epoch_i+1, epoch_count),
                          "Discriminator Loss: {:.4f}...".format(train_loss_d),
                          "Generator Loss: {:.4f}".format(train_loss_g))

                if steps % show_every == 0:
                    show_generator_output(sess, 16, input_z, data_shape[3], data_image_mode)
                    
        show_generator_output(sess, 16, input_z, data_shape[3], data_image_mode)

MNIST

Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.

In [22]:
batch_size = 64
z_dim = 100
learning_rate = 0.001
beta1 = 0.3


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2

mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
          mnist_dataset.shape, mnist_dataset.image_mode)
Epoch 1/2... Discriminator Loss: 7.0308... Generator Loss: 0.0610
Epoch 1/2... Discriminator Loss: 2.9047... Generator Loss: 0.1049
Epoch 1/2... Discriminator Loss: 1.0487... Generator Loss: 2.7417
Epoch 1/2... Discriminator Loss: 1.4915... Generator Loss: 0.3386
Epoch 1/2... Discriminator Loss: 1.5321... Generator Loss: 0.3183
Epoch 1/2... Discriminator Loss: 1.6018... Generator Loss: 3.2807
Epoch 1/2... Discriminator Loss: 1.6009... Generator Loss: 0.2673
Epoch 1/2... Discriminator Loss: 0.8292... Generator Loss: 1.7473
Epoch 1/2... Discriminator Loss: 1.0811... Generator Loss: 2.5695
Epoch 1/2... Discriminator Loss: 0.5760... Generator Loss: 1.2062
Epoch 1/2... Discriminator Loss: 0.9589... Generator Loss: 0.7101
Epoch 1/2... Discriminator Loss: 0.8683... Generator Loss: 0.6984
Epoch 1/2... Discriminator Loss: 0.3601... Generator Loss: 1.6891
Epoch 1/2... Discriminator Loss: 0.5346... Generator Loss: 1.4939
Epoch 1/2... Discriminator Loss: 0.3899... Generator Loss: 2.8991
Epoch 1/2... Discriminator Loss: 1.1486... Generator Loss: 0.5981
Epoch 1/2... Discriminator Loss: 0.6987... Generator Loss: 1.4453
Epoch 1/2... Discriminator Loss: 0.4925... Generator Loss: 1.7477
Epoch 1/2... Discriminator Loss: 0.2523... Generator Loss: 1.9936
Epoch 1/2... Discriminator Loss: 0.5678... Generator Loss: 1.5108
Epoch 1/2... Discriminator Loss: 0.1725... Generator Loss: 2.4675
Epoch 1/2... Discriminator Loss: 2.0000... Generator Loss: 0.2027
Epoch 1/2... Discriminator Loss: 0.9712... Generator Loss: 0.6008
Epoch 1/2... Discriminator Loss: 0.7335... Generator Loss: 0.7914
Epoch 1/2... Discriminator Loss: 0.4959... Generator Loss: 1.8765
Epoch 1/2... Discriminator Loss: 0.5692... Generator Loss: 1.1924
Epoch 1/2... Discriminator Loss: 0.5596... Generator Loss: 1.1748
Epoch 1/2... Discriminator Loss: 1.1201... Generator Loss: 0.5218
Epoch 1/2... Discriminator Loss: 0.4998... Generator Loss: 1.1594
Epoch 1/2... Discriminator Loss: 0.2505... Generator Loss: 1.8644
Epoch 1/2... Discriminator Loss: 0.3093... Generator Loss: 1.6932
Epoch 1/2... Discriminator Loss: 0.2581... Generator Loss: 1.7814
Epoch 1/2... Discriminator Loss: 0.1365... Generator Loss: 2.4889
Epoch 1/2... Discriminator Loss: 0.2480... Generator Loss: 1.8425
Epoch 1/2... Discriminator Loss: 0.1625... Generator Loss: 2.3591
Epoch 1/2... Discriminator Loss: 0.0978... Generator Loss: 2.7137
Epoch 1/2... Discriminator Loss: 1.3105... Generator Loss: 1.8861
Epoch 1/2... Discriminator Loss: 0.7347... Generator Loss: 1.5132
Epoch 1/2... Discriminator Loss: 0.7790... Generator Loss: 0.7524
Epoch 1/2... Discriminator Loss: 1.5869... Generator Loss: 0.3304
Epoch 1/2... Discriminator Loss: 0.5073... Generator Loss: 1.2884
Epoch 1/2... Discriminator Loss: 0.5163... Generator Loss: 1.2136
Epoch 1/2... Discriminator Loss: 0.4170... Generator Loss: 1.3801
Epoch 1/2... Discriminator Loss: 0.2466... Generator Loss: 1.8289
Epoch 1/2... Discriminator Loss: 0.1283... Generator Loss: 2.7913
Epoch 1/2... Discriminator Loss: 0.2051... Generator Loss: 2.0449
Epoch 1/2... Discriminator Loss: 0.2521... Generator Loss: 1.8671
Epoch 1/2... Discriminator Loss: 0.4211... Generator Loss: 1.4127
Epoch 1/2... Discriminator Loss: 0.0100... Generator Loss: 6.4556
Epoch 1/2... Discriminator Loss: 0.0202... Generator Loss: 4.6715
Epoch 1/2... Discriminator Loss: 0.1650... Generator Loss: 2.3949
Epoch 1/2... Discriminator Loss: 0.0813... Generator Loss: 3.1535
Epoch 1/2... Discriminator Loss: 0.0070... Generator Loss: 7.9345
Epoch 1/2... Discriminator Loss: 0.0596... Generator Loss: 3.3923
Epoch 1/2... Discriminator Loss: 0.0242... Generator Loss: 4.4477
Epoch 1/2... Discriminator Loss: 0.0119... Generator Loss: 5.7898
Epoch 1/2... Discriminator Loss: 0.0139... Generator Loss: 7.4763
Epoch 1/2... Discriminator Loss: 0.0333... Generator Loss: 4.3392
Epoch 1/2... Discriminator Loss: 0.2033... Generator Loss: 2.2247
Epoch 1/2... Discriminator Loss: 0.0091... Generator Loss: 5.3904
Epoch 1/2... Discriminator Loss: 0.0582... Generator Loss: 4.4179
Epoch 1/2... Discriminator Loss: 0.0181... Generator Loss: 4.6779
Epoch 1/2... Discriminator Loss: 1.4436... Generator Loss: 0.8073
Epoch 1/2... Discriminator Loss: 1.4758... Generator Loss: 2.2352
Epoch 1/2... Discriminator Loss: 1.1566... Generator Loss: 1.5410
Epoch 1/2... Discriminator Loss: 1.0089... Generator Loss: 1.3953
Epoch 1/2... Discriminator Loss: 1.2736... Generator Loss: 2.1612
Epoch 1/2... Discriminator Loss: 0.8998... Generator Loss: 1.7055
Epoch 1/2... Discriminator Loss: 0.8340... Generator Loss: 1.7556
Epoch 1/2... Discriminator Loss: 0.9599... Generator Loss: 2.5895
Epoch 1/2... Discriminator Loss: 0.6733... Generator Loss: 1.1241
Epoch 1/2... Discriminator Loss: 0.7043... Generator Loss: 1.9982
Epoch 1/2... Discriminator Loss: 1.5203... Generator Loss: 0.3690
Epoch 1/2... Discriminator Loss: 1.4350... Generator Loss: 4.1565
Epoch 1/2... Discriminator Loss: 0.4066... Generator Loss: 1.9715
Epoch 1/2... Discriminator Loss: 0.3964... Generator Loss: 1.5211
Epoch 1/2... Discriminator Loss: 1.0485... Generator Loss: 0.5724
Epoch 1/2... Discriminator Loss: 1.0969... Generator Loss: 0.6838
Epoch 1/2... Discriminator Loss: 0.6342... Generator Loss: 1.0942
Epoch 1/2... Discriminator Loss: 0.8157... Generator Loss: 0.8485
Epoch 1/2... Discriminator Loss: 0.7831... Generator Loss: 1.2226
Epoch 1/2... Discriminator Loss: 0.6236... Generator Loss: 1.8539
Epoch 1/2... Discriminator Loss: 1.0873... Generator Loss: 0.5131
Epoch 1/2... Discriminator Loss: 1.0790... Generator Loss: 3.5376
Epoch 1/2... Discriminator Loss: 0.6321... Generator Loss: 1.0245
Epoch 1/2... Discriminator Loss: 2.6271... Generator Loss: 0.1328
Epoch 1/2... Discriminator Loss: 2.0672... Generator Loss: 4.8793
Epoch 1/2... Discriminator Loss: 0.7609... Generator Loss: 0.7947
Epoch 1/2... Discriminator Loss: 0.4953... Generator Loss: 1.3820
Epoch 1/2... Discriminator Loss: 0.2970... Generator Loss: 1.8231
Epoch 1/2... Discriminator Loss: 0.2497... Generator Loss: 2.0327
Epoch 1/2... Discriminator Loss: 0.6592... Generator Loss: 2.4873
Epoch 1/2... Discriminator Loss: 0.7689... Generator Loss: 0.8546
Epoch 2/2... Discriminator Loss: 0.5034... Generator Loss: 1.2327
Epoch 2/2... Discriminator Loss: 0.2815... Generator Loss: 1.9634
Epoch 2/2... Discriminator Loss: 0.3631... Generator Loss: 1.5472
Epoch 2/2... Discriminator Loss: 0.2577... Generator Loss: 2.1048
Epoch 2/2... Discriminator Loss: 0.1891... Generator Loss: 2.1370
Epoch 2/2... Discriminator Loss: 0.0935... Generator Loss: 2.9792
Epoch 2/2... Discriminator Loss: 0.2741... Generator Loss: 1.8767
Epoch 2/2... Discriminator Loss: 0.1912... Generator Loss: 2.3583
Epoch 2/2... Discriminator Loss: 0.2136... Generator Loss: 2.0756
Epoch 2/2... Discriminator Loss: 0.0398... Generator Loss: 4.2706
Epoch 2/2... Discriminator Loss: 0.0645... Generator Loss: 3.4747
Epoch 2/2... Discriminator Loss: 0.0719... Generator Loss: 3.4209
Epoch 2/2... Discriminator Loss: 0.0370... Generator Loss: 4.2358
Epoch 2/2... Discriminator Loss: 1.1918... Generator Loss: 7.0195
Epoch 2/2... Discriminator Loss: 0.6048... Generator Loss: 2.1508
Epoch 2/2... Discriminator Loss: 0.6969... Generator Loss: 1.0082
Epoch 2/2... Discriminator Loss: 1.6150... Generator Loss: 4.9439
Epoch 2/2... Discriminator Loss: 0.3128... Generator Loss: 1.8513
Epoch 2/2... Discriminator Loss: 0.5087... Generator Loss: 1.3459
Epoch 2/2... Discriminator Loss: 0.6434... Generator Loss: 0.9592
Epoch 2/2... Discriminator Loss: 0.5646... Generator Loss: 1.0941
Epoch 2/2... Discriminator Loss: 0.3140... Generator Loss: 1.7183
Epoch 2/2... Discriminator Loss: 0.2296... Generator Loss: 2.3479
Epoch 2/2... Discriminator Loss: 0.2269... Generator Loss: 2.0922
Epoch 2/2... Discriminator Loss: 0.0353... Generator Loss: 4.3376
Epoch 2/2... Discriminator Loss: 0.0876... Generator Loss: 3.2192
Epoch 2/2... Discriminator Loss: 0.0640... Generator Loss: 3.6214
Epoch 2/2... Discriminator Loss: 0.0766... Generator Loss: 3.2605
Epoch 2/2... Discriminator Loss: 0.0362... Generator Loss: 4.2826
Epoch 2/2... Discriminator Loss: 9.3842... Generator Loss: 12.6295
Epoch 2/2... Discriminator Loss: 0.3932... Generator Loss: 1.5053
Epoch 2/2... Discriminator Loss: 0.3702... Generator Loss: 1.4656
Epoch 2/2... Discriminator Loss: 0.2766... Generator Loss: 1.8894
Epoch 2/2... Discriminator Loss: 0.3668... Generator Loss: 1.5846
Epoch 2/2... Discriminator Loss: 0.0408... Generator Loss: 4.0465
Epoch 2/2... Discriminator Loss: 0.0349... Generator Loss: 4.3576
Epoch 2/2... Discriminator Loss: 0.0395... Generator Loss: 4.2451
Epoch 2/2... Discriminator Loss: 0.0224... Generator Loss: 4.9035
Epoch 2/2... Discriminator Loss: 0.2240... Generator Loss: 2.1506
Epoch 2/2... Discriminator Loss: 0.0359... Generator Loss: 4.0273
Epoch 2/2... Discriminator Loss: 0.0117... Generator Loss: 5.8218
Epoch 2/2... Discriminator Loss: 0.0351... Generator Loss: 4.5086
Epoch 2/2... Discriminator Loss: 0.0539... Generator Loss: 3.4967
Epoch 2/2... Discriminator Loss: 0.0123... Generator Loss: 5.4691
Epoch 2/2... Discriminator Loss: 0.0342... Generator Loss: 4.1605
Epoch 2/2... Discriminator Loss: 0.0061... Generator Loss: 6.6834
Epoch 2/2... Discriminator Loss: 0.0113... Generator Loss: 5.3561
Epoch 2/2... Discriminator Loss: 0.0183... Generator Loss: 4.9665
Epoch 2/2... Discriminator Loss: 0.0429... Generator Loss: 3.8517
Epoch 2/2... Discriminator Loss: 0.1414... Generator Loss: 2.5126
Epoch 2/2... Discriminator Loss: 0.0219... Generator Loss: 4.8702
Epoch 2/2... Discriminator Loss: 0.0468... Generator Loss: 3.8389
Epoch 2/2... Discriminator Loss: 0.0840... Generator Loss: 3.0858
Epoch 2/2... Discriminator Loss: 0.0249... Generator Loss: 4.2903
Epoch 2/2... Discriminator Loss: 0.0350... Generator Loss: 3.9059
Epoch 2/2... Discriminator Loss: 0.0163... Generator Loss: 5.0957
Epoch 2/2... Discriminator Loss: 0.0104... Generator Loss: 5.3820
Epoch 2/2... Discriminator Loss: 0.6718... Generator Loss: 1.0621
Epoch 2/2... Discriminator Loss: 0.3184... Generator Loss: 1.9387
Epoch 2/2... Discriminator Loss: 0.1740... Generator Loss: 2.4949
Epoch 2/2... Discriminator Loss: 0.4913... Generator Loss: 1.3181
Epoch 2/2... Discriminator Loss: 0.2056... Generator Loss: 2.1455
Epoch 2/2... Discriminator Loss: 0.3194... Generator Loss: 4.1135
Epoch 2/2... Discriminator Loss: 0.7514... Generator Loss: 0.9387
Epoch 2/2... Discriminator Loss: 0.4150... Generator Loss: 1.4896
Epoch 2/2... Discriminator Loss: 0.3625... Generator Loss: 1.5726
Epoch 2/2... Discriminator Loss: 0.3072... Generator Loss: 1.7759
Epoch 2/2... Discriminator Loss: 0.5090... Generator Loss: 1.3233
Epoch 2/2... Discriminator Loss: 0.1995... Generator Loss: 2.1828
Epoch 2/2... Discriminator Loss: 0.1480... Generator Loss: 2.5538
Epoch 2/2... Discriminator Loss: 0.2046... Generator Loss: 2.0548
Epoch 2/2... Discriminator Loss: 0.1304... Generator Loss: 2.8011
Epoch 2/2... Discriminator Loss: 0.1415... Generator Loss: 2.6193
Epoch 2/2... Discriminator Loss: 0.0443... Generator Loss: 3.8381
Epoch 2/2... Discriminator Loss: 0.0671... Generator Loss: 3.3280
Epoch 2/2... Discriminator Loss: 0.0392... Generator Loss: 3.8921
Epoch 2/2... Discriminator Loss: 0.1601... Generator Loss: 2.4769
Epoch 2/2... Discriminator Loss: 0.0544... Generator Loss: 3.7800
Epoch 2/2... Discriminator Loss: 0.1393... Generator Loss: 2.6031
Epoch 2/2... Discriminator Loss: 0.1146... Generator Loss: 2.9249
Epoch 2/2... Discriminator Loss: 0.0139... Generator Loss: 5.3945
Epoch 2/2... Discriminator Loss: 0.0441... Generator Loss: 4.0124
Epoch 2/2... Discriminator Loss: 0.0547... Generator Loss: 3.5734
Epoch 2/2... Discriminator Loss: 0.0283... Generator Loss: 4.2886
Epoch 2/2... Discriminator Loss: 0.0246... Generator Loss: 4.5076
Epoch 2/2... Discriminator Loss: 0.0218... Generator Loss: 4.5403
Epoch 2/2... Discriminator Loss: 0.4415... Generator Loss: 3.5111
Epoch 2/2... Discriminator Loss: 0.2895... Generator Loss: 3.2039
Epoch 2/2... Discriminator Loss: 0.2364... Generator Loss: 2.3332
Epoch 2/2... Discriminator Loss: 1.0068... Generator Loss: 1.6447
Epoch 2/2... Discriminator Loss: 0.2577... Generator Loss: 2.0558
Epoch 2/2... Discriminator Loss: 0.2167... Generator Loss: 2.2271
Epoch 2/2... Discriminator Loss: 0.6806... Generator Loss: 1.0550
Epoch 2/2... Discriminator Loss: 1.0890... Generator Loss: 2.3147

CelebA

Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.

In [23]:
batch_size = 64
z_dim = 100
learning_rate = 0.001
beta1 = 0.3


"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2

celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
    train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
          celeba_dataset.shape, celeba_dataset.image_mode)
Epoch 1/2... Discriminator Loss: 4.0395... Generator Loss: 0.1118
Epoch 1/2... Discriminator Loss: 0.2537... Generator Loss: 3.0063
Epoch 1/2... Discriminator Loss: 0.9604... Generator Loss: 3.2365
Epoch 1/2... Discriminator Loss: 1.7782... Generator Loss: 0.2290
Epoch 1/2... Discriminator Loss: 0.4583... Generator Loss: 1.5730
Epoch 1/2... Discriminator Loss: 0.6792... Generator Loss: 3.1756
Epoch 1/2... Discriminator Loss: 0.3157... Generator Loss: 1.8069
Epoch 1/2... Discriminator Loss: 0.2398... Generator Loss: 2.0754
Epoch 1/2... Discriminator Loss: 0.0940... Generator Loss: 3.5597
Epoch 1/2... Discriminator Loss: 3.4955... Generator Loss: 0.0395
Epoch 1/2... Discriminator Loss: 1.8572... Generator Loss: 3.7648
Epoch 1/2... Discriminator Loss: 0.1462... Generator Loss: 2.1617
Epoch 1/2... Discriminator Loss: 7.0654... Generator Loss: 5.9396
Epoch 1/2... Discriminator Loss: 1.1064... Generator Loss: 0.5531
Epoch 1/2... Discriminator Loss: 0.0984... Generator Loss: 5.1921
Epoch 1/2... Discriminator Loss: 0.2176... Generator Loss: 1.8873
Epoch 1/2... Discriminator Loss: 0.0236... Generator Loss: 4.0730
Epoch 1/2... Discriminator Loss: 0.6399... Generator Loss: 0.9115
Epoch 1/2... Discriminator Loss: 1.1822... Generator Loss: 0.7563
Epoch 1/2... Discriminator Loss: 1.4598... Generator Loss: 2.3537
Epoch 1/2... Discriminator Loss: 0.0472... Generator Loss: 3.7271
Epoch 1/2... Discriminator Loss: 0.1141... Generator Loss: 2.6775
Epoch 1/2... Discriminator Loss: 0.0758... Generator Loss: 5.5227
Epoch 1/2... Discriminator Loss: 0.0211... Generator Loss: 6.2572
Epoch 1/2... Discriminator Loss: 2.1500... Generator Loss: 0.1998
Epoch 1/2... Discriminator Loss: 0.0802... Generator Loss: 2.8228
Epoch 1/2... Discriminator Loss: 1.1762... Generator Loss: 0.7584
Epoch 1/2... Discriminator Loss: 0.9287... Generator Loss: 1.9647
Epoch 1/2... Discriminator Loss: 0.0622... Generator Loss: 3.5633
Epoch 1/2... Discriminator Loss: 0.0133... Generator Loss: 5.4210
Epoch 1/2... Discriminator Loss: 1.3805... Generator Loss: 3.5596
Epoch 1/2... Discriminator Loss: 0.0683... Generator Loss: 3.0880
Epoch 1/2... Discriminator Loss: 2.1300... Generator Loss: 1.8281
Epoch 1/2... Discriminator Loss: 1.4478... Generator Loss: 0.5825
Epoch 1/2... Discriminator Loss: 1.2710... Generator Loss: 0.8652
Epoch 1/2... Discriminator Loss: 1.2374... Generator Loss: 0.8962
Epoch 1/2... Discriminator Loss: 1.4185... Generator Loss: 0.4993
Epoch 1/2... Discriminator Loss: 1.4878... Generator Loss: 1.1286
Epoch 1/2... Discriminator Loss: 1.3441... Generator Loss: 1.1205
Epoch 1/2... Discriminator Loss: 1.2683... Generator Loss: 0.8186
Epoch 1/2... Discriminator Loss: 1.3130... Generator Loss: 0.5144
Epoch 1/2... Discriminator Loss: 1.2492... Generator Loss: 0.5614
Epoch 1/2... Discriminator Loss: 1.1397... Generator Loss: 0.7061
Epoch 1/2... Discriminator Loss: 1.4113... Generator Loss: 0.3871
Epoch 1/2... Discriminator Loss: 1.8135... Generator Loss: 0.2197
Epoch 1/2... Discriminator Loss: 1.3864... Generator Loss: 0.9461
Epoch 1/2... Discriminator Loss: 1.1980... Generator Loss: 1.1299
Epoch 1/2... Discriminator Loss: 0.5981... Generator Loss: 1.6948
Epoch 1/2... Discriminator Loss: 0.2407... Generator Loss: 1.8123
Epoch 1/2... Discriminator Loss: 0.7808... Generator Loss: 0.6971
Epoch 1/2... Discriminator Loss: 1.1199... Generator Loss: 1.8925
Epoch 1/2... Discriminator Loss: 0.6560... Generator Loss: 0.8057
Epoch 1/2... Discriminator Loss: 0.0319... Generator Loss: 3.7256
Epoch 1/2... Discriminator Loss: 1.3298... Generator Loss: 0.8281
Epoch 1/2... Discriminator Loss: 1.2963... Generator Loss: 0.7162
Epoch 1/2... Discriminator Loss: 1.3174... Generator Loss: 0.6578
Epoch 1/2... Discriminator Loss: 1.4205... Generator Loss: 0.6482
Epoch 1/2... Discriminator Loss: 1.2931... Generator Loss: 0.7007
Epoch 1/2... Discriminator Loss: 1.3196... Generator Loss: 0.6548
Epoch 1/2... Discriminator Loss: 1.1690... Generator Loss: 0.6107
Epoch 1/2... Discriminator Loss: 1.0166... Generator Loss: 3.5171
Epoch 1/2... Discriminator Loss: 0.6641... Generator Loss: 0.7744
Epoch 1/2... Discriminator Loss: 0.1123... Generator Loss: 2.4859
Epoch 1/2... Discriminator Loss: 0.8038... Generator Loss: 0.9709
Epoch 1/2... Discriminator Loss: 1.4692... Generator Loss: 1.7069
Epoch 1/2... Discriminator Loss: 0.1676... Generator Loss: 2.1638
Epoch 1/2... Discriminator Loss: 0.0348... Generator Loss: 4.1543
Epoch 1/2... Discriminator Loss: 1.6853... Generator Loss: 5.3122
Epoch 1/2... Discriminator Loss: 2.2797... Generator Loss: 2.8523
Epoch 1/2... Discriminator Loss: 0.2359... Generator Loss: 1.7290
Epoch 1/2... Discriminator Loss: 0.3837... Generator Loss: 1.2864
Epoch 1/2... Discriminator Loss: 1.9056... Generator Loss: 1.4942
Epoch 1/2... Discriminator Loss: 1.3000... Generator Loss: 0.6260
Epoch 1/2... Discriminator Loss: 1.3619... Generator Loss: 0.7189
Epoch 1/2... Discriminator Loss: 1.4920... Generator Loss: 0.4345
Epoch 1/2... Discriminator Loss: 1.2748... Generator Loss: 0.7883
Epoch 1/2... Discriminator Loss: 1.5359... Generator Loss: 1.2054
Epoch 1/2... Discriminator Loss: 1.3105... Generator Loss: 0.6263
Epoch 1/2... Discriminator Loss: 1.1989... Generator Loss: 0.6615
Epoch 1/2... Discriminator Loss: 1.1935... Generator Loss: 1.2135
Epoch 1/2... Discriminator Loss: 0.5722... Generator Loss: 6.1850
Epoch 1/2... Discriminator Loss: 0.0476... Generator Loss: 3.4769
Epoch 1/2... Discriminator Loss: 0.0186... Generator Loss: 5.1548
Epoch 1/2... Discriminator Loss: 0.0089... Generator Loss: 5.5915
Epoch 1/2... Discriminator Loss: 0.1572... Generator Loss: 2.2795
Epoch 1/2... Discriminator Loss: 0.0077... Generator Loss: 5.2239
Epoch 1/2... Discriminator Loss: 0.3977... Generator Loss: 1.2917
Epoch 1/2... Discriminator Loss: 3.8517... Generator Loss: 3.4047
Epoch 1/2... Discriminator Loss: 1.2259... Generator Loss: 0.6610
Epoch 1/2... Discriminator Loss: 0.7832... Generator Loss: 0.9940
Epoch 1/2... Discriminator Loss: 1.4234... Generator Loss: 0.3672
Epoch 1/2... Discriminator Loss: 1.7810... Generator Loss: 1.5209
Epoch 1/2... Discriminator Loss: 0.5522... Generator Loss: 0.9319
Epoch 1/2... Discriminator Loss: 1.5337... Generator Loss: 1.7859
Epoch 1/2... Discriminator Loss: 3.4183... Generator Loss: 3.4797
Epoch 1/2... Discriminator Loss: 0.1224... Generator Loss: 3.1438
Epoch 1/2... Discriminator Loss: 0.1099... Generator Loss: 5.2013
Epoch 1/2... Discriminator Loss: 3.0138... Generator Loss: 5.5552
Epoch 1/2... Discriminator Loss: 1.6087... Generator Loss: 0.6274
Epoch 1/2... Discriminator Loss: 1.3899... Generator Loss: 0.6661
Epoch 1/2... Discriminator Loss: 1.3625... Generator Loss: 0.4476
Epoch 1/2... Discriminator Loss: 0.0775... Generator Loss: 3.2108
Epoch 1/2... Discriminator Loss: 1.9667... Generator Loss: 0.3385
Epoch 1/2... Discriminator Loss: 1.4000... Generator Loss: 0.6749
Epoch 1/2... Discriminator Loss: 1.3536... Generator Loss: 0.5638
Epoch 1/2... Discriminator Loss: 1.4119... Generator Loss: 0.9790
Epoch 1/2... Discriminator Loss: 1.3412... Generator Loss: 0.7054
Epoch 1/2... Discriminator Loss: 1.2629... Generator Loss: 0.6639
Epoch 1/2... Discriminator Loss: 1.3918... Generator Loss: 0.5583
Epoch 1/2... Discriminator Loss: 1.4520... Generator Loss: 1.0351
Epoch 1/2... Discriminator Loss: 1.4143... Generator Loss: 0.5759
Epoch 1/2... Discriminator Loss: 1.2783... Generator Loss: 0.9535
Epoch 1/2... Discriminator Loss: 1.2712... Generator Loss: 0.7436
Epoch 1/2... Discriminator Loss: 1.2739... Generator Loss: 0.5790
Epoch 1/2... Discriminator Loss: 1.2732... Generator Loss: 0.8080
Epoch 1/2... Discriminator Loss: 1.3599... Generator Loss: 0.7526
Epoch 1/2... Discriminator Loss: 1.3128... Generator Loss: 0.4959
Epoch 1/2... Discriminator Loss: 1.1583... Generator Loss: 0.6261
Epoch 1/2... Discriminator Loss: 1.2776... Generator Loss: 0.6792
Epoch 1/2... Discriminator Loss: 1.3168... Generator Loss: 0.4820
Epoch 1/2... Discriminator Loss: 1.7850... Generator Loss: 0.2439
Epoch 1/2... Discriminator Loss: 1.2817... Generator Loss: 0.6774
Epoch 1/2... Discriminator Loss: 1.2888... Generator Loss: 0.7761
Epoch 1/2... Discriminator Loss: 1.2109... Generator Loss: 1.8647
Epoch 1/2... Discriminator Loss: 1.3002... Generator Loss: 0.6856
Epoch 1/2... Discriminator Loss: 0.4725... Generator Loss: 1.3790
Epoch 1/2... Discriminator Loss: 2.1057... Generator Loss: 0.4172
Epoch 1/2... Discriminator Loss: 1.2905... Generator Loss: 0.6365
Epoch 1/2... Discriminator Loss: 1.1699... Generator Loss: 0.9742
Epoch 1/2... Discriminator Loss: 1.1263... Generator Loss: 0.5536
Epoch 1/2... Discriminator Loss: 1.3956... Generator Loss: 0.6017
Epoch 1/2... Discriminator Loss: 0.1059... Generator Loss: 3.1764
Epoch 1/2... Discriminator Loss: 1.5089... Generator Loss: 0.6743
Epoch 1/2... Discriminator Loss: 0.7632... Generator Loss: 1.3714
Epoch 1/2... Discriminator Loss: 1.6179... Generator Loss: 3.0838
Epoch 1/2... Discriminator Loss: 1.0002... Generator Loss: 0.9518
Epoch 1/2... Discriminator Loss: 1.0226... Generator Loss: 1.2799
Epoch 1/2... Discriminator Loss: 0.9262... Generator Loss: 0.7545
Epoch 1/2... Discriminator Loss: 0.3904... Generator Loss: 2.5872
Epoch 1/2... Discriminator Loss: 1.3701... Generator Loss: 0.7087
Epoch 1/2... Discriminator Loss: 1.3646... Generator Loss: 0.6979
Epoch 1/2... Discriminator Loss: 1.3220... Generator Loss: 0.7580
Epoch 1/2... Discriminator Loss: 1.3437... Generator Loss: 0.7434
Epoch 1/2... Discriminator Loss: 1.3483... Generator Loss: 0.5854
Epoch 1/2... Discriminator Loss: 1.2697... Generator Loss: 0.8660
Epoch 1/2... Discriminator Loss: 1.3658... Generator Loss: 1.2349
Epoch 1/2... Discriminator Loss: 1.2997... Generator Loss: 0.5092
Epoch 1/2... Discriminator Loss: 1.3077... Generator Loss: 0.5810
Epoch 1/2... Discriminator Loss: 1.5482... Generator Loss: 0.3459
Epoch 1/2... Discriminator Loss: 1.7594... Generator Loss: 0.2615
Epoch 1/2... Discriminator Loss: 0.7210... Generator Loss: 1.0027
Epoch 1/2... Discriminator Loss: 1.4573... Generator Loss: 0.7798
Epoch 1/2... Discriminator Loss: 1.2763... Generator Loss: 0.6854
Epoch 1/2... Discriminator Loss: 1.2702... Generator Loss: 0.7881
Epoch 1/2... Discriminator Loss: 1.2836... Generator Loss: 0.6998
Epoch 1/2... Discriminator Loss: 1.3406... Generator Loss: 0.7586
Epoch 1/2... Discriminator Loss: 1.1972... Generator Loss: 0.7207
Epoch 1/2... Discriminator Loss: 0.6968... Generator Loss: 0.9677
Epoch 1/2... Discriminator Loss: 2.0075... Generator Loss: 0.1815
Epoch 1/2... Discriminator Loss: 0.5928... Generator Loss: 0.9334
Epoch 1/2... Discriminator Loss: 1.4969... Generator Loss: 1.0284
Epoch 1/2... Discriminator Loss: 1.7753... Generator Loss: 0.3179
Epoch 1/2... Discriminator Loss: 1.2979... Generator Loss: 0.4777
Epoch 1/2... Discriminator Loss: 1.3078... Generator Loss: 0.4011
Epoch 1/2... Discriminator Loss: 0.9449... Generator Loss: 1.8881
Epoch 1/2... Discriminator Loss: 3.5910... Generator Loss: 3.8967
Epoch 1/2... Discriminator Loss: 0.2185... Generator Loss: 2.0074
Epoch 1/2... Discriminator Loss: 0.1032... Generator Loss: 2.9202
Epoch 1/2... Discriminator Loss: 0.5141... Generator Loss: 1.0888
Epoch 1/2... Discriminator Loss: 0.1123... Generator Loss: 3.6397
Epoch 1/2... Discriminator Loss: 0.1908... Generator Loss: 2.0453
Epoch 1/2... Discriminator Loss: 0.4561... Generator Loss: 1.1451
Epoch 1/2... Discriminator Loss: 0.1126... Generator Loss: 2.4674
Epoch 1/2... Discriminator Loss: 0.0824... Generator Loss: 2.8133
Epoch 1/2... Discriminator Loss: 0.0095... Generator Loss: 5.6709
Epoch 1/2... Discriminator Loss: 0.0066... Generator Loss: 6.0145
Epoch 1/2... Discriminator Loss: 0.0154... Generator Loss: 4.7317
Epoch 1/2... Discriminator Loss: 0.0292... Generator Loss: 4.0217
Epoch 1/2... Discriminator Loss: 0.1377... Generator Loss: 2.2532
Epoch 1/2... Discriminator Loss: 0.0174... Generator Loss: 4.6741
Epoch 1/2... Discriminator Loss: 0.0110... Generator Loss: 5.0606
Epoch 1/2... Discriminator Loss: 0.0074... Generator Loss: 5.7623
Epoch 1/2... Discriminator Loss: 0.0078... Generator Loss: 5.9805
Epoch 1/2... Discriminator Loss: 0.0425... Generator Loss: 3.5340
Epoch 1/2... Discriminator Loss: 0.0074... Generator Loss: 5.7134
Epoch 1/2... Discriminator Loss: 0.0112... Generator Loss: 5.4670
Epoch 1/2... Discriminator Loss: 0.0146... Generator Loss: 5.0221
Epoch 1/2... Discriminator Loss: 0.0313... Generator Loss: 3.9718
Epoch 1/2... Discriminator Loss: 0.0251... Generator Loss: 4.6256
Epoch 1/2... Discriminator Loss: 0.0487... Generator Loss: 3.4888
Epoch 1/2... Discriminator Loss: 0.0041... Generator Loss: 7.0924
Epoch 1/2... Discriminator Loss: 0.0373... Generator Loss: 3.7476
Epoch 1/2... Discriminator Loss: 0.0333... Generator Loss: 3.8789
Epoch 1/2... Discriminator Loss: 0.0188... Generator Loss: 4.8148
Epoch 1/2... Discriminator Loss: 0.0041... Generator Loss: 8.7101
Epoch 1/2... Discriminator Loss: 1.9135... Generator Loss: 4.4681
Epoch 1/2... Discriminator Loss: 0.3159... Generator Loss: 2.2259
Epoch 1/2... Discriminator Loss: 0.4876... Generator Loss: 3.3747
Epoch 1/2... Discriminator Loss: 1.2145... Generator Loss: 0.5714
Epoch 1/2... Discriminator Loss: 0.9127... Generator Loss: 1.3096
Epoch 1/2... Discriminator Loss: 1.2239... Generator Loss: 0.5154
Epoch 1/2... Discriminator Loss: 1.4638... Generator Loss: 0.3768
Epoch 1/2... Discriminator Loss: 1.9634... Generator Loss: 0.2099
Epoch 1/2... Discriminator Loss: 1.0902... Generator Loss: 0.6966
Epoch 1/2... Discriminator Loss: 1.0729... Generator Loss: 0.6635
Epoch 1/2... Discriminator Loss: 1.2024... Generator Loss: 0.5076
Epoch 1/2... Discriminator Loss: 0.3418... Generator Loss: 1.7138
Epoch 1/2... Discriminator Loss: 1.3607... Generator Loss: 0.6744
Epoch 1/2... Discriminator Loss: 0.7044... Generator Loss: 1.0588
Epoch 1/2... Discriminator Loss: 1.7409... Generator Loss: 0.3064
Epoch 1/2... Discriminator Loss: 0.1241... Generator Loss: 3.0830
Epoch 1/2... Discriminator Loss: 4.1696... Generator Loss: 3.7774
Epoch 1/2... Discriminator Loss: 1.3909... Generator Loss: 0.6706
Epoch 1/2... Discriminator Loss: 1.3008... Generator Loss: 1.0930
Epoch 1/2... Discriminator Loss: 1.3579... Generator Loss: 1.4236
Epoch 1/2... Discriminator Loss: 1.2961... Generator Loss: 0.5075
Epoch 1/2... Discriminator Loss: 1.2592... Generator Loss: 1.2876
Epoch 1/2... Discriminator Loss: 1.6148... Generator Loss: 1.9598
Epoch 1/2... Discriminator Loss: 1.1824... Generator Loss: 0.8047
Epoch 1/2... Discriminator Loss: 1.2370... Generator Loss: 0.4780
Epoch 1/2... Discriminator Loss: 2.8900... Generator Loss: 3.4336
Epoch 1/2... Discriminator Loss: 2.2089... Generator Loss: 0.1501
Epoch 1/2... Discriminator Loss: 1.2765... Generator Loss: 0.5732
Epoch 1/2... Discriminator Loss: 1.1694... Generator Loss: 2.1744
Epoch 1/2... Discriminator Loss: 1.6156... Generator Loss: 0.2927
Epoch 1/2... Discriminator Loss: 1.3160... Generator Loss: 0.3756
Epoch 1/2... Discriminator Loss: 1.4094... Generator Loss: 0.6218
Epoch 1/2... Discriminator Loss: 0.2553... Generator Loss: 1.8612
Epoch 1/2... Discriminator Loss: 0.2643... Generator Loss: 3.4301
Epoch 1/2... Discriminator Loss: 0.3818... Generator Loss: 1.5122
Epoch 1/2... Discriminator Loss: 1.2629... Generator Loss: 0.6982
Epoch 1/2... Discriminator Loss: 1.2857... Generator Loss: 0.5494
Epoch 1/2... Discriminator Loss: 0.6906... Generator Loss: 0.9458
Epoch 1/2... Discriminator Loss: 1.3385... Generator Loss: 0.9351
Epoch 1/2... Discriminator Loss: 1.3231... Generator Loss: 0.5893
Epoch 1/2... Discriminator Loss: 1.3642... Generator Loss: 0.4483
Epoch 1/2... Discriminator Loss: 1.2391... Generator Loss: 1.0992
Epoch 1/2... Discriminator Loss: 1.2462... Generator Loss: 0.4641
Epoch 1/2... Discriminator Loss: 1.0959... Generator Loss: 0.7610
Epoch 1/2... Discriminator Loss: 0.8578... Generator Loss: 1.3155
Epoch 1/2... Discriminator Loss: 1.1292... Generator Loss: 1.3126
Epoch 1/2... Discriminator Loss: 0.3503... Generator Loss: 1.4965
Epoch 1/2... Discriminator Loss: 2.9774... Generator Loss: 5.5447
Epoch 1/2... Discriminator Loss: 1.1715... Generator Loss: 0.4956
Epoch 1/2... Discriminator Loss: 0.1344... Generator Loss: 2.6729
Epoch 1/2... Discriminator Loss: 1.1079... Generator Loss: 0.5192
Epoch 1/2... Discriminator Loss: 0.2799... Generator Loss: 2.4198
Epoch 1/2... Discriminator Loss: 0.5475... Generator Loss: 1.7348
Epoch 1/2... Discriminator Loss: 1.0061... Generator Loss: 0.5608
Epoch 1/2... Discriminator Loss: 0.0526... Generator Loss: 3.5500
Epoch 1/2... Discriminator Loss: 1.3424... Generator Loss: 0.3756
Epoch 1/2... Discriminator Loss: 1.5547... Generator Loss: 0.6131
Epoch 1/2... Discriminator Loss: 0.3967... Generator Loss: 2.5695
Epoch 1/2... Discriminator Loss: 0.0930... Generator Loss: 2.8405
Epoch 1/2... Discriminator Loss: 1.4838... Generator Loss: 1.0106
Epoch 1/2... Discriminator Loss: 1.2353... Generator Loss: 0.8128
Epoch 1/2... Discriminator Loss: 1.2490... Generator Loss: 1.0070
Epoch 1/2... Discriminator Loss: 1.5823... Generator Loss: 0.2910
Epoch 1/2... Discriminator Loss: 1.1023... Generator Loss: 0.7549
Epoch 1/2... Discriminator Loss: 0.4264... Generator Loss: 1.6317
Epoch 1/2... Discriminator Loss: 1.3171... Generator Loss: 0.4263
Epoch 1/2... Discriminator Loss: 1.8393... Generator Loss: 1.9646
Epoch 1/2... Discriminator Loss: 1.8062... Generator Loss: 0.2315
Epoch 1/2... Discriminator Loss: 1.7004... Generator Loss: 0.2526
Epoch 1/2... Discriminator Loss: 0.6840... Generator Loss: 1.1527
Epoch 1/2... Discriminator Loss: 0.3726... Generator Loss: 1.7080
Epoch 1/2... Discriminator Loss: 1.1253... Generator Loss: 1.6996
Epoch 1/2... Discriminator Loss: 1.3471... Generator Loss: 2.1396
Epoch 1/2... Discriminator Loss: 0.8787... Generator Loss: 0.9167
Epoch 1/2... Discriminator Loss: 2.5328... Generator Loss: 3.8118
Epoch 1/2... Discriminator Loss: 1.0949... Generator Loss: 0.7134
Epoch 1/2... Discriminator Loss: 1.1815... Generator Loss: 1.1210
Epoch 1/2... Discriminator Loss: 1.2279... Generator Loss: 0.4994
Epoch 1/2... Discriminator Loss: 0.9673... Generator Loss: 0.6403
Epoch 1/2... Discriminator Loss: 0.8148... Generator Loss: 1.2079
Epoch 1/2... Discriminator Loss: 2.3241... Generator Loss: 3.4636
Epoch 1/2... Discriminator Loss: 1.3385... Generator Loss: 0.5181
Epoch 1/2... Discriminator Loss: 1.3545... Generator Loss: 0.4021
Epoch 1/2... Discriminator Loss: 1.0309... Generator Loss: 1.0416
Epoch 1/2... Discriminator Loss: 1.1256... Generator Loss: 0.5928
Epoch 1/2... Discriminator Loss: 1.7181... Generator Loss: 0.2547
Epoch 1/2... Discriminator Loss: 0.9905... Generator Loss: 0.7363
Epoch 1/2... Discriminator Loss: 1.6737... Generator Loss: 0.2947
Epoch 1/2... Discriminator Loss: 1.1836... Generator Loss: 0.5332
Epoch 1/2... Discriminator Loss: 0.8900... Generator Loss: 1.7344
Epoch 1/2... Discriminator Loss: 1.4827... Generator Loss: 0.3676
Epoch 1/2... Discriminator Loss: 1.0854... Generator Loss: 0.9032
Epoch 1/2... Discriminator Loss: 1.5325... Generator Loss: 0.3096
Epoch 1/2... Discriminator Loss: 0.5704... Generator Loss: 3.0253
Epoch 1/2... Discriminator Loss: 1.6116... Generator Loss: 0.3053
Epoch 1/2... Discriminator Loss: 1.0743... Generator Loss: 0.5462
Epoch 1/2... Discriminator Loss: 0.1073... Generator Loss: 3.3433
Epoch 1/2... Discriminator Loss: 1.3431... Generator Loss: 0.5459
Epoch 1/2... Discriminator Loss: 1.0941... Generator Loss: 0.6397
Epoch 1/2... Discriminator Loss: 1.1084... Generator Loss: 0.5929
Epoch 1/2... Discriminator Loss: 0.5949... Generator Loss: 1.0735
Epoch 1/2... Discriminator Loss: 1.0672... Generator Loss: 1.8186
Epoch 1/2... Discriminator Loss: 2.5447... Generator Loss: 0.0996
Epoch 1/2... Discriminator Loss: 0.5226... Generator Loss: 1.2951
Epoch 1/2... Discriminator Loss: 0.7740... Generator Loss: 0.8733
Epoch 1/2... Discriminator Loss: 2.0583... Generator Loss: 2.2984
Epoch 1/2... Discriminator Loss: 0.8991... Generator Loss: 0.6875
Epoch 1/2... Discriminator Loss: 0.4997... Generator Loss: 1.2392
Epoch 1/2... Discriminator Loss: 0.2894... Generator Loss: 2.4126
Epoch 1/2... Discriminator Loss: 1.1987... Generator Loss: 0.5844
Epoch 1/2... Discriminator Loss: 1.2079... Generator Loss: 0.5821
Epoch 1/2... Discriminator Loss: 1.3241... Generator Loss: 0.7119
Epoch 1/2... Discriminator Loss: 1.5565... Generator Loss: 0.3273
Epoch 1/2... Discriminator Loss: 1.0714... Generator Loss: 0.5105
Epoch 1/2... Discriminator Loss: 1.0922... Generator Loss: 0.7016
Epoch 1/2... Discriminator Loss: 1.4428... Generator Loss: 0.3468
Epoch 1/2... Discriminator Loss: 0.4497... Generator Loss: 1.3714
Epoch 1/2... Discriminator Loss: 1.1831... Generator Loss: 0.5350
Epoch 1/2... Discriminator Loss: 0.8668... Generator Loss: 1.0300
Epoch 1/2... Discriminator Loss: 0.3934... Generator Loss: 1.7947
Epoch 1/2... Discriminator Loss: 1.5768... Generator Loss: 0.3050
Epoch 2/2... Discriminator Loss: 1.2353... Generator Loss: 0.4518
Epoch 2/2... Discriminator Loss: 1.2876... Generator Loss: 0.3936
Epoch 2/2... Discriminator Loss: 1.2144... Generator Loss: 0.5850
Epoch 2/2... Discriminator Loss: 0.5132... Generator Loss: 1.5842
Epoch 2/2... Discriminator Loss: 1.7412... Generator Loss: 0.2686
Epoch 2/2... Discriminator Loss: 0.7635... Generator Loss: 1.8079
Epoch 2/2... Discriminator Loss: 1.4295... Generator Loss: 0.3893
Epoch 2/2... Discriminator Loss: 1.1018... Generator Loss: 0.5263
Epoch 2/2... Discriminator Loss: 1.0755... Generator Loss: 0.6923
Epoch 2/2... Discriminator Loss: 1.2082... Generator Loss: 0.5553
Epoch 2/2... Discriminator Loss: 0.9870... Generator Loss: 1.3316
Epoch 2/2... Discriminator Loss: 1.3942... Generator Loss: 0.3724
Epoch 2/2... Discriminator Loss: 1.1828... Generator Loss: 0.4917
Epoch 2/2... Discriminator Loss: 1.3370... Generator Loss: 0.3702
Epoch 2/2... Discriminator Loss: 0.6360... Generator Loss: 0.8912
Epoch 2/2... Discriminator Loss: 2.5358... Generator Loss: 0.1070
Epoch 2/2... Discriminator Loss: 0.6615... Generator Loss: 2.2101
Epoch 2/2... Discriminator Loss: 1.2451... Generator Loss: 1.0273
Epoch 2/2... Discriminator Loss: 0.3293... Generator Loss: 1.8389
Epoch 2/2... Discriminator Loss: 0.5730... Generator Loss: 1.0020
Epoch 2/2... Discriminator Loss: 0.6847... Generator Loss: 1.1568
Epoch 2/2... Discriminator Loss: 1.7654... Generator Loss: 2.5824
Epoch 2/2... Discriminator Loss: 0.6438... Generator Loss: 0.9628
Epoch 2/2... Discriminator Loss: 1.5424... Generator Loss: 0.3268
Epoch 2/2... Discriminator Loss: 1.2906... Generator Loss: 0.8810
Epoch 2/2... Discriminator Loss: 0.5242... Generator Loss: 1.2874
Epoch 2/2... Discriminator Loss: 0.9156... Generator Loss: 0.8550
Epoch 2/2... Discriminator Loss: 0.9063... Generator Loss: 1.3263
Epoch 2/2... Discriminator Loss: 1.0519... Generator Loss: 0.5896
Epoch 2/2... Discriminator Loss: 2.2771... Generator Loss: 0.1410
Epoch 2/2... Discriminator Loss: 0.1981... Generator Loss: 3.0001
Epoch 2/2... Discriminator Loss: 3.0598... Generator Loss: 4.1015
Epoch 2/2... Discriminator Loss: 0.6353... Generator Loss: 1.0720
Epoch 2/2... Discriminator Loss: 1.3460... Generator Loss: 0.4946
Epoch 2/2... Discriminator Loss: 0.9783... Generator Loss: 1.0797
Epoch 2/2... Discriminator Loss: 1.7434... Generator Loss: 2.1406
Epoch 2/2... Discriminator Loss: 1.1579... Generator Loss: 0.4930
Epoch 2/2... Discriminator Loss: 0.8029... Generator Loss: 1.7020
Epoch 2/2... Discriminator Loss: 0.9806... Generator Loss: 0.6420
Epoch 2/2... Discriminator Loss: 1.2256... Generator Loss: 0.4534
Epoch 2/2... Discriminator Loss: 1.3279... Generator Loss: 0.4298
Epoch 2/2... Discriminator Loss: 1.5995... Generator Loss: 0.2906
Epoch 2/2... Discriminator Loss: 0.3595... Generator Loss: 1.8381
Epoch 2/2... Discriminator Loss: 1.6089... Generator Loss: 2.5774
Epoch 2/2... Discriminator Loss: 1.1053... Generator Loss: 1.3411
Epoch 2/2... Discriminator Loss: 1.2228... Generator Loss: 1.1506
Epoch 2/2... Discriminator Loss: 1.4976... Generator Loss: 0.3325
Epoch 2/2... Discriminator Loss: 1.0380... Generator Loss: 0.5614
Epoch 2/2... Discriminator Loss: 1.5515... Generator Loss: 0.3047
Epoch 2/2... Discriminator Loss: 0.8949... Generator Loss: 0.7714
Epoch 2/2... Discriminator Loss: 0.6136... Generator Loss: 1.9782
Epoch 2/2... Discriminator Loss: 1.2933... Generator Loss: 0.5064
Epoch 2/2... Discriminator Loss: 0.7288... Generator Loss: 1.6378
Epoch 2/2... Discriminator Loss: 0.4917... Generator Loss: 1.1024
Epoch 2/2... Discriminator Loss: 1.2863... Generator Loss: 0.4300
Epoch 2/2... Discriminator Loss: 1.9695... Generator Loss: 0.2190
Epoch 2/2... Discriminator Loss: 1.2977... Generator Loss: 0.5092
Epoch 2/2... Discriminator Loss: 1.7406... Generator Loss: 2.5422
Epoch 2/2... Discriminator Loss: 0.7245... Generator Loss: 0.8438
Epoch 2/2... Discriminator Loss: 1.0336... Generator Loss: 0.5455
Epoch 2/2... Discriminator Loss: 1.0920... Generator Loss: 1.1844
Epoch 2/2... Discriminator Loss: 1.0678... Generator Loss: 0.6903
Epoch 2/2... Discriminator Loss: 1.2368... Generator Loss: 0.4519
Epoch 2/2... Discriminator Loss: 1.8360... Generator Loss: 0.2220
Epoch 2/2... Discriminator Loss: 0.8188... Generator Loss: 1.0912
Epoch 2/2... Discriminator Loss: 0.5222... Generator Loss: 1.2505
Epoch 2/2... Discriminator Loss: 0.9346... Generator Loss: 0.7768
Epoch 2/2... Discriminator Loss: 1.3107... Generator Loss: 0.4825
Epoch 2/2... Discriminator Loss: 1.1125... Generator Loss: 1.3489
Epoch 2/2... Discriminator Loss: 1.1962... Generator Loss: 0.8380
Epoch 2/2... Discriminator Loss: 0.9099... Generator Loss: 1.0670
Epoch 2/2... Discriminator Loss: 1.2398... Generator Loss: 2.3170
Epoch 2/2... Discriminator Loss: 1.8816... Generator Loss: 0.2031
Epoch 2/2... Discriminator Loss: 1.1616... Generator Loss: 2.0512
Epoch 2/2... Discriminator Loss: 0.8891... Generator Loss: 1.1340
Epoch 2/2... Discriminator Loss: 0.8318... Generator Loss: 0.7406
Epoch 2/2... Discriminator Loss: 2.1854... Generator Loss: 3.4305
Epoch 2/2... Discriminator Loss: 1.6271... Generator Loss: 0.2966
Epoch 2/2... Discriminator Loss: 1.1600... Generator Loss: 0.5676
Epoch 2/2... Discriminator Loss: 0.5397... Generator Loss: 1.5164
Epoch 2/2... Discriminator Loss: 2.0377... Generator Loss: 0.1704
Epoch 2/2... Discriminator Loss: 0.8581... Generator Loss: 1.1460
Epoch 2/2... Discriminator Loss: 0.8602... Generator Loss: 1.9195
Epoch 2/2... Discriminator Loss: 1.0071... Generator Loss: 3.4298
Epoch 2/2... Discriminator Loss: 0.3190... Generator Loss: 1.5075
Epoch 2/2... Discriminator Loss: 0.9660... Generator Loss: 1.2155
Epoch 2/2... Discriminator Loss: 0.7648... Generator Loss: 1.2785
Epoch 2/2... Discriminator Loss: 2.0388... Generator Loss: 0.1829
Epoch 2/2... Discriminator Loss: 1.6339... Generator Loss: 0.2918
Epoch 2/2... Discriminator Loss: 0.9217... Generator Loss: 0.8268
Epoch 2/2... Discriminator Loss: 1.5682... Generator Loss: 2.5218
Epoch 2/2... Discriminator Loss: 0.4327... Generator Loss: 1.3512
Epoch 2/2... Discriminator Loss: 1.1611... Generator Loss: 1.1489
Epoch 2/2... Discriminator Loss: 1.7918... Generator Loss: 0.2422
Epoch 2/2... Discriminator Loss: 1.4805... Generator Loss: 0.3396
Epoch 2/2... Discriminator Loss: 0.7374... Generator Loss: 0.8365
Epoch 2/2... Discriminator Loss: 1.6774... Generator Loss: 0.2654
Epoch 2/2... Discriminator Loss: 0.7459... Generator Loss: 1.6230
Epoch 2/2... Discriminator Loss: 0.6922... Generator Loss: 0.9459
Epoch 2/2... Discriminator Loss: 0.9068... Generator Loss: 1.1125
Epoch 2/2... Discriminator Loss: 0.7799... Generator Loss: 0.9551
Epoch 2/2... Discriminator Loss: 0.5981... Generator Loss: 0.9949
Epoch 2/2... Discriminator Loss: 1.5152... Generator Loss: 0.3867
Epoch 2/2... Discriminator Loss: 1.1968... Generator Loss: 0.4638
Epoch 2/2... Discriminator Loss: 0.7856... Generator Loss: 0.8443
Epoch 2/2... Discriminator Loss: 1.5131... Generator Loss: 0.3223
Epoch 2/2... Discriminator Loss: 1.6807... Generator Loss: 0.2750
Epoch 2/2... Discriminator Loss: 0.6040... Generator Loss: 1.9635
Epoch 2/2... Discriminator Loss: 1.2254... Generator Loss: 2.5619
Epoch 2/2... Discriminator Loss: 1.9586... Generator Loss: 0.2326
Epoch 2/2... Discriminator Loss: 1.4198... Generator Loss: 1.6270
Epoch 2/2... Discriminator Loss: 0.3699... Generator Loss: 2.3521
Epoch 2/2... Discriminator Loss: 1.0188... Generator Loss: 0.6344
Epoch 2/2... Discriminator Loss: 1.6514... Generator Loss: 2.2900
Epoch 2/2... Discriminator Loss: 1.4001... Generator Loss: 0.3667
Epoch 2/2... Discriminator Loss: 1.5652... Generator Loss: 0.3067
Epoch 2/2... Discriminator Loss: 0.7101... Generator Loss: 0.9527
Epoch 2/2... Discriminator Loss: 0.3769... Generator Loss: 1.8612
Epoch 2/2... Discriminator Loss: 0.1915... Generator Loss: 2.3329
Epoch 2/2... Discriminator Loss: 2.3673... Generator Loss: 0.1219
Epoch 2/2... Discriminator Loss: 0.9862... Generator Loss: 0.7717
Epoch 2/2... Discriminator Loss: 0.7689... Generator Loss: 1.3144
Epoch 2/2... Discriminator Loss: 1.7064... Generator Loss: 0.2692
Epoch 2/2... Discriminator Loss: 0.7668... Generator Loss: 1.4410
Epoch 2/2... Discriminator Loss: 0.4450... Generator Loss: 1.4916
Epoch 2/2... Discriminator Loss: 0.4650... Generator Loss: 1.4878
Epoch 2/2... Discriminator Loss: 1.2318... Generator Loss: 0.4462
Epoch 2/2... Discriminator Loss: 0.5180... Generator Loss: 1.0915
Epoch 2/2... Discriminator Loss: 0.7829... Generator Loss: 1.9876
Epoch 2/2... Discriminator Loss: 1.9149... Generator Loss: 0.2254
Epoch 2/2... Discriminator Loss: 1.4069... Generator Loss: 0.4104
Epoch 2/2... Discriminator Loss: 1.4629... Generator Loss: 0.3464
Epoch 2/2... Discriminator Loss: 1.3454... Generator Loss: 0.3707
Epoch 2/2... Discriminator Loss: 2.3818... Generator Loss: 0.1506
Epoch 2/2... Discriminator Loss: 0.8477... Generator Loss: 1.2043
Epoch 2/2... Discriminator Loss: 0.7523... Generator Loss: 1.2928
Epoch 2/2... Discriminator Loss: 1.2151... Generator Loss: 0.5165
Epoch 2/2... Discriminator Loss: 0.6263... Generator Loss: 1.0014
Epoch 2/2... Discriminator Loss: 1.2009... Generator Loss: 2.1174
Epoch 2/2... Discriminator Loss: 0.8635... Generator Loss: 0.7093
Epoch 2/2... Discriminator Loss: 0.2873... Generator Loss: 2.0701
Epoch 2/2... Discriminator Loss: 1.0191... Generator Loss: 0.5792
Epoch 2/2... Discriminator Loss: 1.2975... Generator Loss: 0.7098
Epoch 2/2... Discriminator Loss: 1.0343... Generator Loss: 0.6508
Epoch 2/2... Discriminator Loss: 2.0390... Generator Loss: 0.2066
Epoch 2/2... Discriminator Loss: 0.9368... Generator Loss: 1.7604
Epoch 2/2... Discriminator Loss: 2.6123... Generator Loss: 0.0974
Epoch 2/2... Discriminator Loss: 1.8010... Generator Loss: 0.2503
Epoch 2/2... Discriminator Loss: 1.6692... Generator Loss: 0.2822
Epoch 2/2... Discriminator Loss: 1.0791... Generator Loss: 2.0099
Epoch 2/2... Discriminator Loss: 0.7345... Generator Loss: 1.2399
Epoch 2/2... Discriminator Loss: 0.7747... Generator Loss: 1.1724
Epoch 2/2... Discriminator Loss: 1.1184... Generator Loss: 0.6488
Epoch 2/2... Discriminator Loss: 1.6707... Generator Loss: 0.2945
Epoch 2/2... Discriminator Loss: 0.3442... Generator Loss: 2.5329
Epoch 2/2... Discriminator Loss: 1.1924... Generator Loss: 0.4560
Epoch 2/2... Discriminator Loss: 1.1167... Generator Loss: 0.5101
Epoch 2/2... Discriminator Loss: 1.2421... Generator Loss: 2.8878
Epoch 2/2... Discriminator Loss: 1.4599... Generator Loss: 0.3603
Epoch 2/2... Discriminator Loss: 0.2544... Generator Loss: 1.9268
Epoch 2/2... Discriminator Loss: 1.0475... Generator Loss: 1.3328
Epoch 2/2... Discriminator Loss: 0.6628... Generator Loss: 1.1932
Epoch 2/2... Discriminator Loss: 0.2762... Generator Loss: 1.9649
Epoch 2/2... Discriminator Loss: 1.6087... Generator Loss: 0.4076
Epoch 2/2... Discriminator Loss: 0.3364... Generator Loss: 1.7219
Epoch 2/2... Discriminator Loss: 1.0619... Generator Loss: 2.3855
Epoch 2/2... Discriminator Loss: 1.3472... Generator Loss: 0.5078
Epoch 2/2... Discriminator Loss: 0.6418... Generator Loss: 0.9210
Epoch 2/2... Discriminator Loss: 1.1004... Generator Loss: 1.4857
Epoch 2/2... Discriminator Loss: 1.4527... Generator Loss: 0.3642
Epoch 2/2... Discriminator Loss: 0.8623... Generator Loss: 4.4302
Epoch 2/2... Discriminator Loss: 1.1964... Generator Loss: 0.4840
Epoch 2/2... Discriminator Loss: 1.4148... Generator Loss: 0.4217
Epoch 2/2... Discriminator Loss: 0.8015... Generator Loss: 0.8391
Epoch 2/2... Discriminator Loss: 1.6653... Generator Loss: 0.2634
Epoch 2/2... Discriminator Loss: 0.8884... Generator Loss: 1.0362
Epoch 2/2... Discriminator Loss: 1.1598... Generator Loss: 0.5108
Epoch 2/2... Discriminator Loss: 2.0791... Generator Loss: 0.2069
Epoch 2/2... Discriminator Loss: 1.3204... Generator Loss: 0.4056
Epoch 2/2... Discriminator Loss: 1.2539... Generator Loss: 0.5209
Epoch 2/2... Discriminator Loss: 0.7530... Generator Loss: 1.1653
Epoch 2/2... Discriminator Loss: 2.1839... Generator Loss: 3.6884
Epoch 2/2... Discriminator Loss: 0.9946... Generator Loss: 0.7983
Epoch 2/2... Discriminator Loss: 0.7561... Generator Loss: 1.0188
Epoch 2/2... Discriminator Loss: 0.4196... Generator Loss: 1.3993
Epoch 2/2... Discriminator Loss: 1.8320... Generator Loss: 0.2300
Epoch 2/2... Discriminator Loss: 0.9988... Generator Loss: 0.7875
Epoch 2/2... Discriminator Loss: 0.5713... Generator Loss: 1.0603
Epoch 2/2... Discriminator Loss: 1.1095... Generator Loss: 2.8714
Epoch 2/2... Discriminator Loss: 1.8925... Generator Loss: 0.2006
Epoch 2/2... Discriminator Loss: 0.9545... Generator Loss: 1.4449
Epoch 2/2... Discriminator Loss: 1.5765... Generator Loss: 0.2983
Epoch 2/2... Discriminator Loss: 1.9958... Generator Loss: 0.1842
Epoch 2/2... Discriminator Loss: 2.6203... Generator Loss: 0.1137
Epoch 2/2... Discriminator Loss: 0.7514... Generator Loss: 0.8678
Epoch 2/2... Discriminator Loss: 0.8476... Generator Loss: 0.6867
Epoch 2/2... Discriminator Loss: 0.5887... Generator Loss: 1.1917
Epoch 2/2... Discriminator Loss: 1.0817... Generator Loss: 0.7690
Epoch 2/2... Discriminator Loss: 0.9234... Generator Loss: 0.7309
Epoch 2/2... Discriminator Loss: 0.9085... Generator Loss: 0.6770
Epoch 2/2... Discriminator Loss: 1.7453... Generator Loss: 0.2842
Epoch 2/2... Discriminator Loss: 0.7169... Generator Loss: 1.0633
Epoch 2/2... Discriminator Loss: 2.2451... Generator Loss: 4.0774
Epoch 2/2... Discriminator Loss: 1.2840... Generator Loss: 0.4759
Epoch 2/2... Discriminator Loss: 1.7870... Generator Loss: 0.2439
Epoch 2/2... Discriminator Loss: 1.8234... Generator Loss: 0.3144
Epoch 2/2... Discriminator Loss: 1.1498... Generator Loss: 0.6169
Epoch 2/2... Discriminator Loss: 0.6676... Generator Loss: 2.8991
Epoch 2/2... Discriminator Loss: 2.4693... Generator Loss: 0.1215
Epoch 2/2... Discriminator Loss: 1.8141... Generator Loss: 0.2446
Epoch 2/2... Discriminator Loss: 1.2311... Generator Loss: 0.4797
Epoch 2/2... Discriminator Loss: 1.6063... Generator Loss: 0.3131
Epoch 2/2... Discriminator Loss: 1.5346... Generator Loss: 0.3026
Epoch 2/2... Discriminator Loss: 0.7735... Generator Loss: 1.2414
Epoch 2/2... Discriminator Loss: 1.4329... Generator Loss: 0.3750
Epoch 2/2... Discriminator Loss: 0.9500... Generator Loss: 0.7242
Epoch 2/2... Discriminator Loss: 1.0936... Generator Loss: 1.2021
Epoch 2/2... Discriminator Loss: 0.6155... Generator Loss: 0.9681
Epoch 2/2... Discriminator Loss: 1.8723... Generator Loss: 0.2616
Epoch 2/2... Discriminator Loss: 0.9638... Generator Loss: 0.9406
Epoch 2/2... Discriminator Loss: 0.9009... Generator Loss: 0.8998
Epoch 2/2... Discriminator Loss: 1.1203... Generator Loss: 0.5132
Epoch 2/2... Discriminator Loss: 0.4190... Generator Loss: 2.6266
Epoch 2/2... Discriminator Loss: 0.2099... Generator Loss: 2.0362
Epoch 2/2... Discriminator Loss: 0.4391... Generator Loss: 1.6753
Epoch 2/2... Discriminator Loss: 1.2760... Generator Loss: 1.7285
Epoch 2/2... Discriminator Loss: 0.8779... Generator Loss: 0.7943
Epoch 2/2... Discriminator Loss: 2.1654... Generator Loss: 0.1674
Epoch 2/2... Discriminator Loss: 0.5932... Generator Loss: 3.4567
Epoch 2/2... Discriminator Loss: 0.7952... Generator Loss: 0.7586
Epoch 2/2... Discriminator Loss: 0.2710... Generator Loss: 1.8720
Epoch 2/2... Discriminator Loss: 1.2120... Generator Loss: 2.3681
Epoch 2/2... Discriminator Loss: 0.9694... Generator Loss: 0.8069
Epoch 2/2... Discriminator Loss: 2.0272... Generator Loss: 0.1849
Epoch 2/2... Discriminator Loss: 0.6813... Generator Loss: 1.6121
Epoch 2/2... Discriminator Loss: 0.2418... Generator Loss: 1.8966
Epoch 2/2... Discriminator Loss: 0.4488... Generator Loss: 2.3633
Epoch 2/2... Discriminator Loss: 0.8260... Generator Loss: 1.9370
Epoch 2/2... Discriminator Loss: 1.2389... Generator Loss: 0.4769
Epoch 2/2... Discriminator Loss: 0.7600... Generator Loss: 1.1748
Epoch 2/2... Discriminator Loss: 0.4558... Generator Loss: 2.2407
Epoch 2/2... Discriminator Loss: 2.6696... Generator Loss: 0.1106
Epoch 2/2... Discriminator Loss: 1.2495... Generator Loss: 0.4336
Epoch 2/2... Discriminator Loss: 1.0704... Generator Loss: 0.5674
Epoch 2/2... Discriminator Loss: 0.4564... Generator Loss: 1.3098
Epoch 2/2... Discriminator Loss: 0.7272... Generator Loss: 1.4797
Epoch 2/2... Discriminator Loss: 0.8104... Generator Loss: 1.6582
Epoch 2/2... Discriminator Loss: 0.9824... Generator Loss: 0.6749
Epoch 2/2... Discriminator Loss: 0.7311... Generator Loss: 0.9922
Epoch 2/2... Discriminator Loss: 0.2049... Generator Loss: 2.6900
Epoch 2/2... Discriminator Loss: 3.1453... Generator Loss: 0.0653
Epoch 2/2... Discriminator Loss: 0.9453... Generator Loss: 0.9615
Epoch 2/2... Discriminator Loss: 0.7264... Generator Loss: 1.1406
Epoch 2/2... Discriminator Loss: 2.0984... Generator Loss: 0.1853
Epoch 2/2... Discriminator Loss: 0.6997... Generator Loss: 1.1450
Epoch 2/2... Discriminator Loss: 0.8939... Generator Loss: 0.7541
Epoch 2/2... Discriminator Loss: 0.7545... Generator Loss: 1.1559
Epoch 2/2... Discriminator Loss: 0.6782... Generator Loss: 1.3315
Epoch 2/2... Discriminator Loss: 0.4149... Generator Loss: 1.3556
Epoch 2/2... Discriminator Loss: 2.6670... Generator Loss: 4.6748
Epoch 2/2... Discriminator Loss: 1.4163... Generator Loss: 0.4146
Epoch 2/2... Discriminator Loss: 0.4754... Generator Loss: 1.2501
Epoch 2/2... Discriminator Loss: 0.4959... Generator Loss: 1.3076
Epoch 2/2... Discriminator Loss: 1.8153... Generator Loss: 0.2266
Epoch 2/2... Discriminator Loss: 0.9470... Generator Loss: 0.7592
Epoch 2/2... Discriminator Loss: 0.8754... Generator Loss: 0.9449
Epoch 2/2... Discriminator Loss: 2.4192... Generator Loss: 0.1459
Epoch 2/2... Discriminator Loss: 1.4956... Generator Loss: 0.3322
Epoch 2/2... Discriminator Loss: 0.9592... Generator Loss: 2.2708
Epoch 2/2... Discriminator Loss: 0.8872... Generator Loss: 1.1393
Epoch 2/2... Discriminator Loss: 0.7187... Generator Loss: 0.8796
Epoch 2/2... Discriminator Loss: 0.8035... Generator Loss: 2.0939
Epoch 2/2... Discriminator Loss: 0.9789... Generator Loss: 0.8628
Epoch 2/2... Discriminator Loss: 0.7869... Generator Loss: 1.0742
Epoch 2/2... Discriminator Loss: 0.7278... Generator Loss: 0.9143
Epoch 2/2... Discriminator Loss: 0.1698... Generator Loss: 2.0749
Epoch 2/2... Discriminator Loss: 0.8027... Generator Loss: 0.7591
Epoch 2/2... Discriminator Loss: 1.3222... Generator Loss: 2.0423
Epoch 2/2... Discriminator Loss: 0.9690... Generator Loss: 2.4504
Epoch 2/2... Discriminator Loss: 0.7213... Generator Loss: 0.9661
Epoch 2/2... Discriminator Loss: 0.8458... Generator Loss: 0.8015
Epoch 2/2... Discriminator Loss: 1.4371... Generator Loss: 0.3662
Epoch 2/2... Discriminator Loss: 0.5209... Generator Loss: 1.2842
Epoch 2/2... Discriminator Loss: 1.7736... Generator Loss: 2.7544
Epoch 2/2... Discriminator Loss: 0.6699... Generator Loss: 0.9077
Epoch 2/2... Discriminator Loss: 0.4984... Generator Loss: 1.1580
Epoch 2/2... Discriminator Loss: 1.2000... Generator Loss: 0.5388
Epoch 2/2... Discriminator Loss: 0.7743... Generator Loss: 1.3579
Epoch 2/2... Discriminator Loss: 0.6528... Generator Loss: 1.7023
Epoch 2/2... Discriminator Loss: 0.8559... Generator Loss: 0.7911
Epoch 2/2... Discriminator Loss: 0.7752... Generator Loss: 0.9169
Epoch 2/2... Discriminator Loss: 0.8720... Generator Loss: 1.4733
Epoch 2/2... Discriminator Loss: 2.1422... Generator Loss: 0.1730
Epoch 2/2... Discriminator Loss: 0.2431... Generator Loss: 2.1281
Epoch 2/2... Discriminator Loss: 1.6625... Generator Loss: 0.3297
Epoch 2/2... Discriminator Loss: 0.6469... Generator Loss: 1.4123
Epoch 2/2... Discriminator Loss: 0.7123... Generator Loss: 0.8807
Epoch 2/2... Discriminator Loss: 2.2787... Generator Loss: 0.1339
Epoch 2/2... Discriminator Loss: 1.7788... Generator Loss: 0.2481
Epoch 2/2... Discriminator Loss: 1.6575... Generator Loss: 0.2753
Epoch 2/2... Discriminator Loss: 1.2959... Generator Loss: 0.4547
Epoch 2/2... Discriminator Loss: 0.3845... Generator Loss: 1.4514
Epoch 2/2... Discriminator Loss: 0.6118... Generator Loss: 1.8383
Epoch 2/2... Discriminator Loss: 0.8994... Generator Loss: 0.9859
Epoch 2/2... Discriminator Loss: 1.0677... Generator Loss: 0.6173
Epoch 2/2... Discriminator Loss: 0.4504... Generator Loss: 1.2863
Epoch 2/2... Discriminator Loss: 2.6080... Generator Loss: 0.1092
Epoch 2/2... Discriminator Loss: 1.0077... Generator Loss: 0.5732
Epoch 2/2... Discriminator Loss: 0.3381... Generator Loss: 1.6613
Epoch 2/2... Discriminator Loss: 0.3164... Generator Loss: 1.5524
Epoch 2/2... Discriminator Loss: 1.4670... Generator Loss: 1.8885
Epoch 2/2... Discriminator Loss: 0.8112... Generator Loss: 0.9562
Epoch 2/2... Discriminator Loss: 1.7491... Generator Loss: 0.2649
Epoch 2/2... Discriminator Loss: 0.8635... Generator Loss: 0.9226
Epoch 2/2... Discriminator Loss: 0.7018... Generator Loss: 1.0634
Epoch 2/2... Discriminator Loss: 1.2503... Generator Loss: 3.5388
Epoch 2/2... Discriminator Loss: 1.2467... Generator Loss: 0.4363

Submitting This Project

When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.